General principles and design overview of digital predistortion

Braithwaite, R. Neil

doi:10.1017/cbo9780511744839.007

Cited by 32 publications

(18 citation statements)

References 23 publications

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“…Following a closed-loop error minimization technique as in [18], the coefficients can be extracted iteratively finding the LS solution. At the nth iteration (i.e., when considering buffers of N data samples), the coefficients are obtained as where G 0 determines the desired linear gain of the PA, and where y and u are the N × 1 vectors of the PA output and the transmitted input, respectively.…”

Section: Digital Predistortion Adaptation Pathmentioning

confidence: 99%

Independent Digital Predistortion Parameters Estimation Using Adaptive Principal Component Analysis

López‐Bueno

Pham

Montoro

et al. 2018

IEEE Trans. Microwave Theory Techn.

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This paper presents an estimation/adaptation method based on the adaptive principal component analysis (APCA) technique to guarantee the identification of the minimum necessary parameters of a digital predistorter. The proposed estimation/adaptation technique is suitable for online field-programmable gate array or system on chip implementation. By exploiting the orthogonality of the resulting transformed matrix obtained with the APCA technique, it is possible to reduce the number of coefficients to be estimated which, at the same time, has a beneficial regularization effect by preventing illconditioning or overfitting problems. Therefore, this identification/adaptation method enhances the robustness of the parameter estimation and simplifies the adaptation by reducing the number of estimated coefficients. Due to the orthogonality of the new basis, these parameters can be estimated independently, thus allowing for scalability. Experimental results will show that it is possible to determine the minimum number of parameters to be estimated in order to meet the targeted linearity levels while ensuring a robust well-conditioned identification. Moreover, the results will show how thanks to the orthogonality property of the new basis functions, the coefficients of the digital predistorter can be estimated independently. This allows to tradeoff the digital predistorter adaptation time versus performance and hardware complexity.

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Section: Digital Predistortion Adaptation Pathmentioning

confidence: 99%

Independent Digital Predistortion Parameters Estimation Using Adaptive Principal Component Analysis

López‐Bueno

Pham

Montoro

et al. 2018

IEEE Trans. Microwave Theory Techn.

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“…This is another cross-term, which is similar to the envelope memory polynomial [3] or the gain polynomial model [30]. We define it as the 2 nd -order type-2 term.…”

Section:  Higher-order Extension and Variationsmentioning

confidence: 99%

Decomposed Vector Rotation-Based Behavioral Modeling for Digital Predistortion <newline/>of RF Power Amplifiers

Zhu

2015

IEEE Trans. Microwave Theory Techn.

152

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“…GMP has been chosen since it outperformed MP and DDR-Volterra in our scenario. For parameter estimation, our DPD scheme followed the direct learning (DL) approach [8], using the linear least squares (LS) solution as the estimation method because while the DPD function is nonlinear, it is linear in the parameters. DL was chosen instead of the simpler and widely used indirect learning architecture because it performs better [9]- [10].…”

Section: Preliminary Digital Linearization Architecturementioning

confidence: 99%

Amping Up, Saving Power: Digital Predistortion Linearization Strategies for Power Amplifiers Under Wideband 4G\/5G Burst-Like Waveform Operation

et al. 2016

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ourth-generation (4G) communication systems based on orthogonal frequency division multiplexing (OFDM) and the proposed backwards compatible fifthgeneration (5G) variants, like filter-bank multi-carrier (FBMC), are based on modulation techniques that allow significantly increased spectral efficiency and capacity in mobile radio access networks (RANs). However, the use of these modulation techniques impacts the requirements of the radio base stations, which have been traditionally the most energy consuming-element of mobile networks, accounting for up to 80% of the energy consumption of RANs [1]. Non-constant envelope-modulation techniques with high peak-to-average power ratios (PAPRs) require highly linear power amplifier (PA) amplitude and phase responses to fulfill stringent spectral mask and modulation accuracy requirements. This is often achieved with significant PA back-off, which considerably reduces PA efficiency because the PA's maximum efficiency is achieved near the saturation point. The adoption of gallium nitride (GaN) PA technologies and use of digital linearization techniques are playing a key role in building more efficient base

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General principles and design overview of digital predistortion

Cited by 32 publications

References 23 publications

Independent Digital Predistortion Parameters Estimation Using Adaptive Principal Component Analysis

Independent Digital Predistortion Parameters Estimation Using Adaptive Principal Component Analysis

Decomposed Vector Rotation-Based Behavioral Modeling for Digital Predistortion <newline/>of RF Power Amplifiers

Amping Up, Saving Power: Digital Predistortion Linearization Strategies for Power Amplifiers Under Wideband 4G\/5G Burst-Like Waveform Operation

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